ProLIF Protein-Protein Interface Fingerprinting Skill

SkillDev tools

ProLIF protein-protein trajectory analysis skill for interface interaction fingerprints and stability profiling.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the ProLIF Protein-Protein Interface Fingerprinting Skill skill

What this skill tells your AI

The instructions your AI receives, as published by internscience/molclaw in skills/L1_tools/molclaw-prolif-protein-protein/SKILL.md and read by ahel’s review.

Note:

  • Local files are not directly accessible by the server. Please upload them to the server using molclaw-file-transfer before execution.
  • For PDB file inputs, it is recommended to preprocess them using molclaw-pdbfixer before execution.
  • Please refer to skill molclaw-scp-server to complete tool invocation.

[!NOTE] Local files are not directly accessible by the server. Please upload them to the server using molclaw-file-transfer before execution. For PDB file inputs, it is recommended to preprocess them using molclaw-pdbfixer before execution.

Task Description

Analyze protein-protein interaction trajectories and generate interface interaction fingerprints. Use this skill to evaluate interface stability and identify key residue contributions across simulation.

Routing note: This tool is the primary choice for protein-protein trajectory interface profiling (multi-frame analysis). For single-structure protein-protein interface analysis, use molclaw-interaction-visualizer in protein mode instead — it produces interface heatmaps, network diagrams, and decision-ready JSON.

Input Source Mapping

ParameterSource Guidance
topology_pathSystem topology from MD tools: e.g., protein_openmm_md, prepare_protein_md, goca_pipeline
trajectory_pathTrajectory from the same MD tools, containing dynamic information for both protein chains
selection_aUser-defined selection string for protein chain A, for example segid A or protein and chainid A
selection_bUser-defined selection string for protein chain B, for example segid B or protein and chainid B

Usage

Tool: prolif_protein_protein

Analyze a protein-protein trajectory and return interaction fingerprints or counts with summary metrics.
Args:
    topology_path (str): Path to the system topology file.
    trajectory_path (str): Path to the trajectory file.
    selection_a (str): Selection string for partner A.
    selection_b (str): Selection string for partner B.
    interactions (List[str]|None): Optional interaction types to compute.
    count (bool): If True, compute interaction counts instead of fingerprints. Default: False.
    vicinity_cutoff (float|None): Optional distance cutoff for vicinity interactions.
    params_json (str|None): Optional JSON parameter file path for ProLIF interaction settings.
    start (int|None): Optional start frame index.
    stop (int|None): Optional stop frame index (exclusive).
    step (int|None): Optional frame stride.
Return:
    status (str): 'success' or 'error'.
    msg (str): Human-readable summary or error message.
    command (str): The executed command label ('protein-protein').
    output_dir (str|None): Run-specific directory under tool_result/prolif_result.
    output_file (str|None): Path to the generated CSV file.
    n_frames (int|None): Number of processed frames.
    n_interactions (int|None): Number of interaction columns in output.
    frequent_interactions (List[dict]|None): High-frequency interactions (>30%) with keys 'interaction' and 'frequency'.
    result_summary (dict|None): Full summary dictionary from the wrapper.

How To Use prolif_protein_protein

response = await client.session.call_tool(
    "prolif_protein_protein",
    arguments={
        "topology_path": "relative/path/to/system.prmtop",
        "trajectory_path": "relative/path/to/md.nc",
        "selection_a": "segid A",
        "selection_b": "segid B",
        "start": 0,
        "step": 10
    }
)
result = client.parse_result(response)
key_output = result["output_file"]

Example Parameter Sets

# 1) Main mode
{
    "topology_path": "relative/path/to/system.prmtop",
    "trajectory_path": "relative/path/to/md.nc",
    "selection_a": "segid A",
    "selection_b": "segid B",
    "start": 0,
    "step": 10
}

# 2) Variant mode
{
    "topology_path": "relative/path/to/system.prmtop",
    "trajectory_path": "relative/path/to/md.nc",
    "selection_a": "protein and chainid A",
    "selection_b": "protein and chainid B",
    "count": True,
    "vicinity_cutoff": 3.5,
    "stop": 200
}

Signals

GitHub stars
33
Forks
3
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
molclaw-prolif-protein-protein
Source
github.com/internscience/molclaw